Method of metrology and associated apparatuses

ABSTRACT

Disclosed is a method of, and associated apparatus for, determining an edge position relating to an edge of a feature comprised within an image, such as a scanning electron microscope image, which comprises noise. The method comprises determining a reference signal from said image; and determining said edge position with respect to said reference signal. The reference signal may be determined from the image by applying a  1 -dimensional low-pass filter to the image in a direction parallel to an initial contour estimating the edge position.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority of EP application 18163680.4 which wasfiled on Mar. 23, 2018, and which is incorporated herein in its entiretyby reference.

BACKGROUND Field

The embodiments of the present disclosure relate to methods andapparatus for applying patterns to a substrate in a lithographicprocess, and measurement thereof.

Background

A lithographic apparatus is a machine that applies a desired patternonto a substrate, usually onto a target portion of the substrate. Alithographic apparatus can be used, for example, in the manufacture ofintegrated circuits (ICs). In that instance, a patterning device, whichis alternatively referred to as a mask or a reticle, may be used togenerate a circuit pattern to be formed on an individual layer of theIC. This pattern can be transferred onto a target portion (e.g.comprising part of, one, or several dies) on a substrate (e.g. a siliconwafer). Transfer of the pattern is typically via imaging onto a layer ofradiation-sensitive material (resist) provided on the substrate. Ingeneral, a single substrate will contain a network of adjacent targetportions that are successively patterned. Known lithographic apparatusinclude so-called steppers, in which each target portion is irradiatedby exposing an entire pattern onto the target portion at one time, andso-called scanners, in which each target portion is irradiated byscanning the pattern through a radiation beam in a given direction (the“scanning”-direction) while synchronously scanning the substrateparallel or anti-parallel to this direction. It is also possible totransfer the pattern from the patterning device to the substrate byimprinting the pattern onto the substrate.

In order to monitor the lithographic process, parameters of thepatterned substrate are measured. Parameters may include, for example,the overlay error between successive layers formed in or on thepatterned substrate and critical linewidth or critical dimension (CD) ofdeveloped photosensitive resist. This measurement may be performed on aproduct substrate or on a dedicated metrology target. There are varioustechniques for making measurements of the microscopic structures formedin lithographic processes, including the use of scanning electronmicroscopes and various specialized tools.

In performing lithographic processes, such as application of a patternon a substrate or measurement of such a pattern, process control methodsare used to monitor and control the process. Such process controltechniques are typically performed to obtain corrections for control ofthe lithographic process. It would be desirable to improve such processcontrol methods.

SUMMARY

The embodiments of the present disclosure provide a method ofdetermining an edge position relating to an edge of a feature comprisedwithin an image which comprises noise; said method comprising:determining a reference signal from said image; and determining saidedge position with respect to said reference signal.

The embodiments of the present disclosure provide a computing apparatuscomprising a processor, and being configured to perform the method ofdetermining an edge position relating to an edge of a feature comprisedwithin an image which comprises noise; said method comprising:determining a reference signal from said image; and determining saidedge position with respect to said reference signal.

The embodiments of the present disclosure provide a scanning electronmicroscopy inspection apparatus being operable to image a plurality offeatures on a substrate, and comprising the computing apparatus of thesecond aspect.

The embodiments of the present disclosure provide a computer programcomprising program instructions operable to perform the method ofdetermining an edge position relating to an edge of a feature comprisedwithin an image which comprises noise; said method comprising:determining a reference signal from said image; and determining saidedge position with respect to said reference signal.

Further aspects, features and advantages of the disclosed embodiments,as well as the structure and operation thereof, are described in detailbelow with reference to the accompanying drawings. It is noted that thescope is not limited to the specific embodiments described herein. Suchembodiments are presented herein for illustrative purposes only.Additional embodiments will be apparent to persons skilled in therelevant art(s) based on the teachings contained herein.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the present disclosure will now be described, by way ofexample, with reference to the following drawings.

FIG. 1 depicts a lithographic apparatus together with other apparatusesforming a production facility for semiconductor devices, consistent withembodiments of the present disclosure.

FIG. 2 is a first example flow diagram depicting an exemplary method,consistent with embodiments of the present disclosure.

FIG. 3 is a plot of a reference SEM signal following a first and seconditeration of the exemplary method, consistent with embodiments of thepresent disclosure.

FIG. 4 is a second example flow diagram depicting an exemplary method,consistent with embodiments of the present disclosure.

DETAILED DESCRIPTION

Before describing embodiments in detail, it is instructive to present anexample environment in which the embodiments of the present disclosuremay be implemented.

FIG. 1 at 200 shows a lithographic apparatus LA as part of an industrialproduction facility implementing a high-volume, lithographicmanufacturing process. In the present example, the manufacturing processis adapted for the manufacture of semiconductor products (integratedcircuits) on substrates such as semiconductor wafers. The skilled personwill appreciate that a wide variety of products can be manufactured byprocessing different types of substrates in variants of this process.The production of semiconductor products is used purely as an examplewhich has great commercial significance today.

Within the lithographic apparatus (or “litho tool” 200 for short), ameasurement station MEA is shown at 202 and an exposure station EXP isshown at 204. A control unit LACU is shown at 206. In this example, eachsubstrate visits the measurement station and the exposure station tohave a pattern applied. In an optical lithographic apparatus, forexample, a projection system is used to transfer a product pattern froma patterning device MA onto the substrate using conditioned radiationand a projection system. This is done by forming an image of the patternin a layer of radiation-sensitive resist material.

The term “projection system” used herein should be broadly interpretedas encompassing any type of projection system, including refractive,reflective, catadioptric, magnetic, electromagnetic and electrostaticoptical systems, or any combination thereof, as appropriate for theexposure radiation being used, or for other factors such as the use ofan immersion liquid or the use of a vacuum. The patterning MA device maybe a mask or reticle, which imparts a pattern to a radiation beamtransmitted or reflected by the patterning device. Well-known modes ofoperation include a stepping mode and a scanning mode. As is well known,the projection system may cooperate with support and positioning systemsfor the substrate and the patterning device in a variety of ways toapply a desired pattern to many target portions across a substrate.Programmable patterning devices may be used instead of reticles having afixed pattern. The radiation for example may include electromagneticradiation in the deep ultraviolet (DUV) or extreme ultraviolet (EUV)wavebands. The present disclosure is also applicable to other types oflithographic process, for example imprint lithography and direct writinglithography, for example by electron beam.

The lithographic apparatus control unit LACU which controls all themovements and measurements of various actuators and sensors to receivesubstrates W and reticles MA and to implement the patterning operations.LACU also includes signal processing and data processing capacity toimplement desired calculations relevant to the operation of theapparatus. In practice, control unit LACU will be realized as a systemof many sub-units, each handling the real-time data acquisition,processing and control of a subsystem or component within the apparatus.

Before the pattern is applied to a substrate at the exposure stationEXP, the substrate is processed in at the measurement station MEA sothat various preparatory steps may be carried out. The preparatory stepsmay include mapping the surface height of the substrate using a levelsensor and measuring the position of alignment marks on the substrateusing an alignment sensor. The alignment marks are arranged nominally ina regular grid pattern. However, due to inaccuracies in creating themarks and also due to deformations of the substrate that occurthroughout its processing, the marks deviate from the ideal grid.Consequently, in addition to measuring position and orientation of thesubstrate, the alignment sensor in practice must measure in detail thepositions of many marks across the substrate area, if the apparatus isto print product features at the correct locations with very highaccuracy. The apparatus may be of a so-called dual stage type which hastwo substrate tables, each with a positioning system controlled by thecontrol unit LACU. While one substrate on one substrate table is beingexposed at the exposure station EXP, another substrate can be loadedonto the other substrate table at the measurement station MEA so thatvarious preparatory steps may be carried out. The measurement ofalignment marks is therefore very time-consuming and the provision oftwo substrate tables enables a substantial increase in the throughput ofthe apparatus. If the position sensor IF is not capable of measuring theposition of the substrate table while it is at the measurement stationas well as at the exposure station, a second position sensor may beprovided to enable the positions of the substrate table to be tracked atboth stations. Lithographic apparatus LA may for example be of aso-called dual stage type which has two substrate tables and twostations—an exposure station and a measurement station—between which thesubstrate tables can be exchanged.

Within the production facility, apparatus 200 forms part of a “lithocell” or “litho cluster” that contains also a coating apparatus 208 forapplying photosensitive resist and other coatings to substrates W forpatterning by the apparatus 200. At an output side of apparatus 200, abaking apparatus 210 and developing apparatus 212 are provided fordeveloping the exposed pattern into a physical resist pattern. Betweenall of these apparatuses, substrate handling systems take care ofsupporting the substrates and transferring them from one piece ofapparatus to the next. These apparatuses, which are often collectivelyreferred to as the track, are under the control of a track control unitwhich is itself controlled by a supervisory control system SCS, whichalso controls the lithographic apparatus via lithographic apparatuscontrol unit LACU. Thus, the different apparatus can be operated tomaximize throughput and processing efficiency. Supervisory controlsystem SCS receives recipe information R which provides in great detaila definition of the steps to be performed to create each patternedsubstrate.

Once the pattern has been applied and developed in the litho cell,patterned substrates 220 are transferred to other processing apparatusessuch as are illustrated at 222, 224, 226. A wide range of processingsteps is implemented by various apparatuses in a typical manufacturingfacility. For the sake of example, apparatus 222 in this embodiment isan etching station, and apparatus 224 performs a post-etch annealingstep. Further physical or chemical processing steps are applied infurther apparatuses, 226, etc. Numerous types of operation can berequired to make a real device, such as deposition of material,modification of surface material characteristics (oxidation, doping, ionimplantation etc.), chemical-mechanical polishing (CMP), and so forth.The apparatus 226 may, in practice, represent a series of differentprocessing steps performed in one or more apparatuses. As anotherexample, apparatus and processing steps may be provided for theimplementation of self-aligned multiple patterning, to produce multiplesmaller features based on a precursor pattern laid down by thelithographic apparatus.

As is well known, the manufacture of semiconductor devices involves manyrepetitions of such processing, to build up device structures withappropriate materials and patterns, layer-by-layer on the substrate.Accordingly, substrates 230 arriving at the litho cluster may be newlyprepared substrates, or they may be substrates that have been processedpreviously in this cluster or in another apparatus entirely. Similarly,depending on the required processing, substrates 232 on leavingapparatus 226 may be returned for a subsequent patterning operation inthe same litho cluster, they may be destined for patterning operationsin a different cluster, or they may be finished products to be sent fordicing and packaging.

Each layer of the product structure can utilize a different set ofprocess steps, and the apparatuses 226 used at each layer may becompletely different in type. Further, even where the processing stepsto be applied by the apparatus 226 are nominally the same, in a largefacility, there may be several supposedly identical machines working inparallel to perform the step 226 on different substrates. Smalldifferences in set-up or faults between these machines can mean thatthey influence different substrates in different ways. Even steps thatare relatively common to each layer, such as etching (apparatus 222) maybe implemented by several etching apparatuses that are nominallyidentical but working in parallel to maximize throughput. In practice,moreover, different layers require different etch processes, for examplechemical etches, plasma etches, according to the details of the materialto be etched, and special requirements such as, for example, anisotropicetching.

The previous or subsequent processes may be performed in otherlithography apparatuses, as just mentioned, and may even be performed indifferent types of lithography apparatus. For example, some layers inthe device manufacturing process which are very demanding in parameterssuch as resolution and overlay may be performed in a more advancedlithography tool than other layers that are less demanding. Therefore,some layers may be exposed in an immersion type lithography tool, whileothers are exposed in a ‘dry’ tool. Some layers may be exposed in a toolworking at DUV wavelengths, while others are exposed using EUVwavelength radiation.

In order that the substrates that are exposed by the lithographicapparatus are exposed correctly and consistently, it is desirable toinspect exposed substrates to measure properties such as overlay errorsbetween subsequent layers, line thicknesses, critical dimensions (CD),etc. Accordingly a manufacturing facility in which litho cell LC islocated also includes metrology system which receives some or all of thesubstrates W that have been processed in the litho cell. Metrologyresults are provided directly or indirectly to the supervisory controlsystem SCS. If errors are detected, adjustments may be made to exposuresof subsequent substrates, especially if the metrology can be done soonand fast enough that other substrates of the same batch are still to beexposed. Also, already exposed substrates may be stripped and reworkedto improve yield, or discarded, thereby avoiding performing furtherprocessing on substrates that are known to be faulty. In a case whereonly some target portions of a substrate are faulty, further exposurescan be performed only on those target portions which are good.

Also shown in FIG. 1 is a metrology apparatus 240 which is provided formaking measurements of parameters of the products at desired stages inthe manufacturing process. A common example of a metrology station in amodern lithographic production facility is a scatterometer, for examplea dark-field scatterometer, an angle-resolved scatterometer or aspectroscopic scatterometer, and it may be applied to measure propertiesof the developed substrates at 220 prior to etching in the apparatus222. Using metrology apparatus 240, it may be determined, for example,that important performance parameters such as overlay or criticaldimension (CD) do not meet specified accuracy requirements in thedeveloped resist. Prior to the etching step, the opportunity exists tostrip the developed resist and reprocess the substrates 220 through thelitho cluster. The metrology results 242 from the apparatus 240 can beused to maintain accurate performance of the patterning operations inthe litho cluster, by supervisory control system SCS or control unitLACU 206 making small adjustments over time, thereby minimizing the riskof products being made out-of-specification, and requiring re-work.

Additionally, metrology apparatus 240 or other metrology apparatuses(not shown) can be applied to measure properties of the processedsubstrates 232, 234, and incoming substrates 230. The metrologyapparatus can be used on the processed substrate to determine importantparameters such as overlay or CD.

Another example of a metrology station is a scanning electron microscope(SEM), otherwise referred to as an electron beam (e-beam) metrologydevice, which may be included in addition to, or as an alternative to, ascatterometer. As such, metrology apparatus 240 may comprise an e-beamor SEM metrology device, either alone or in addition to a scatterometer.E-beam and SEM metrology devices have the advantage of measuringfeatures directly (e.g., they directly image the features), rather thanthe indirect measurement techniques used in scatterometry (whereparameter values are determined from reconstruction from or asymmetry indiffraction orders of radiation diffracted by the structure beingmeasured). The main disadvantage with e-beam or SEM metrology devices istheir measurement speed, which is much slower than scatterometry,limiting their potential application to specific offline monitoringprocesses.

Critical dimension scanning electron microscopy (CD-SEM) is a techniquewidely used for substrate and mask metrology in the semiconductorindustry. In CD-SEM, low energy electrons (<1 keV) are acceleratedtowards a surface into which they subsequently diffuse. Secondary orbackscattered electrons emitted by surface atoms excited by the electronbeam are detected by a detector. The number of these detected electronsdepends, among other things, on specimen topography. This is done fordifferent excitation positions on the surface (e.g., by scanning theelectron beam over the surface), to obtain an image. Such a CD-SEM imagemay have a spatial resolution in the order of a nanometer, unparalleledby other metrology techniques employed in this industry. However, theremay be a certain amount of noise in such an image.

A major application of CD-SEM is to observe geometrical edges offeatures (e.g., formed on the substrate in a lithographic process). Indoing this, it may be particularly challenging to accurately determinethe geometrical shape and position of a feature from a noisy SEM image.There are a number of methods known to improve edge-detection in thepresence of significant noise. One such approach uses edge-detectionalgorithms, which typically smooth/filter the image to reduce the noise;however, in doing this they also affect how the edge is perceived.Alternatively, more noise-robust algorithms make use of reference-SEMsignals obtained from a reference geometrical edge, which issubsequently fitted in SEM images. Such an approach, for example, isdescribed in T. Verduin, et al., J. Micro/Nanolith. MEMS MOEMS, 13033009 (2014), and C. A. Mack, et al., Proc. SPIE 10145, 101451R (2017),both of which are incorporated herein by reference. The validity ofthese algorithms is questionable, however, when there is significantdiscrepancy between the reference-SEM signal and the actual SEM signal.Moreover, a fixed reference does not account for local changes in theSEM signal, which may arise from a varying feature shape. An improvedapproach may comprise extracting the reference-SEM signal fromcomparable features, by averaging the SEM signal parallel to the edge ofa reference target. Such a technique is described in patent U.S. Pat.No. 7,269,287 B2, incorporated herein by reference in its entirety. Thisapproach, however, excludes local variations in the reference-SEMsignal, which may arise as a result of local distortions of the feature.As such, this method uses prior knowledge regarding the edge position ofthe feature of interest.

Therefore, a method is proposed which obtains the reference-SEM signalfrom the SEM image itself, rather than a reference image. This meansthat the proposed method is independent of the sample materials and theSEM settings used. As such, the method allows for local variations inthe geometry of both edge shape and position and can iterativelycompensate for LER (line edge roughness) and SEM-induced drifts in theedge position.

The proposed method is illustrated by the flow diagram of FIG. 2. FIG.2(a) comprises a representation of a CD-SEM image showing part of afeature 300 (e.g., a line) having an edge 305 defining it from anadjacent trench 310. The edge 305 has a roughness (i.e., LER) andadditionally, is noisy. The method comprises firstly making an initialestimate of the edge position. In this specific example, illustrated inFIG. 2(b), the estimated position is simply a straight line roughly atthe position of the edge to be detected, this line being defined as theinitial contour 315 (represented by the white dotted line). However, theinitial estimate may comprise any contour; e.g., a rough tracing of theedge. At a next step, illustrated by FIG. 2(c), an area comprisingeither side of this initial contour 315 is selected and shown on a spacetransformed in relation to the contour (i.e., a graph of parallel to thecontour against perpendicular to the contour). This area may be, forexample, a few nanometers (e.g., less than 10 nm, or less than 5 nm)either side of contour 315. In this specific example, because theinitial contour 315 is a straight line, the plot of FIG. 2(c) (roughly)follows the edge profile which is to be determined. FIG. 2(d)illustrates the result of the next step in which a 1-dimensional lowpass filter, e.g., Gaussian smoothing or a Gaussian blur, is applied inthe direction parallel to the contour. It should be understood that theGaussian filter is applied parallel to all points along the contour,i.e., the direction of blurring changes with the direction of thecontour (e.g., when not a straight line). As the filter is only appliedparallel to the contour, blurring perpendicular to the actual edge isminor. The result of this step is used as a reference-SEM signal 320.More specifically, the columns (of the reference-SEM signal 320 of FIG.2(d) are assumed to be the local reference-SEM signals. Each columnwidth may be, for example, defined as a pixel width of the images. Thecolumns of the smoothed reference-SEM signals of FIG. 2(d) arefitted/matched to the corresponding columns of FIG. 2(c), allowing onlya shift in height difference between corresponding columns. As such,this step comprises a 1-dimensional cross correlation between the(noisy) imaged edge (FIG. 2(c)) and the smoothed (filtered) edge FIG.2(d), performed on a column-by-column basis, wherein the columns arealigned (matched) perpendicular to the contour 315. As the comparison ismade using a local reference, possible variations in the edge shape arealso taken into account. The obtained shifts of the column heightsrepresent the displacements due to LER and, as illustrated in FIG. 2(e),are used to define an updated contour 325. In this way, the updated linecontour is based upon reference-SEM signal 320 determined from theactual image. As can be seen in FIG. 2(f), the updated line contour(dotted white line) is a much better match to the actual feature edge305.

Determining the edge contour (a matched contour) based only on areference-SEM signal 320 from the image itself may not be desirable.Therefore, in some embodiments, an additional thresholding step may beperformed on the fitted/matched contour immediately after the matchingstep (matching the reference-SEM signal 320 to the initial contour 315),to obtain a thresholded contour. The thresholded contour may represent abetter estimate of the edge position being determined than the matched(unthresholded) contour. This thresholding step may be performed foreach individual column of the matched reference-SEM signal. Thethresholding may comprise determining a threshold value (e.g., grayvalue) which defines the edge location (according to any suitablecriteria) and using the threshold value to further define the edge basedon the matched image FIG. 3(d) as matched to FIG. 3(c). The concept ofthresholding is well known in the art of edge detection and will not bedescribed in any detail here. The thresholding may additionally comprisescaling the minimum and maximum value per column individually to preventthresholding artifacts which may typically appear when normalizing theminimum and maximum in an area with varying strengths of the SEM signal.The result is an updated contour 325 which is determined from acombination of matching using a reference-SEM signal 320 obtained fromthe actual image and a thresholding step on the matched image.

In some embodiments, the method may be performed iteratively to improvethe edge profile estimate. This comprises repeating the above stepsusing the updated contour 325 as an input contour (initial contour). Thesteps of a second iteration are shown in FIGS. 2(g)-2(i). FIG. 2(g) is aplot of the area transformed around updated contour 325 (i.e., a graphof parallel to the contour against perpendicular to the contour). Asthis contour is now closely matched to the edge profile, this graphshows variation which is close to horizontal. FIG. 2(h) is the smoothedreference-SEM signal following Gaussian smoothing applied parallel tothe updated contour 325. Finally, following the matching step and anythresholding, a second iteration updated contour 330 is obtained, asshown in FIG. 2(i).

A comparison of first iteration contour 325 to the initial contour 315comprises a measure of the LER, while a comparison of the seconditeration contour 330 to the first iteration contour 325 shows mostlyrandom noise, other than a few small trends. Indeed, first iterationcontour 325 and second iteration contour 330 look very much alike, withthe latter only slightly improved compared to the former. Thisimprovement is not necessarily trivial, however, as illustrated by thegraph of FIG. 3. This is an example of the reference-SEM signal after afirst iteration 340 and after a second iteration 350. From this graph,some discrepancy between the two iterations is evident. As might beexpected, the reference-SEM signal in the first iteration 340 issomewhat “rounded off” near the maximum and minimum compared to that ofthe second iteration 350.

The previous example shows how a (local) reference-SEM signals can beobtained from a SEM image and how this concept may be used iterativelyto compensate for severe LER. As a complementary example, theapplication of the method to a very different experimental CD-SEM imageis shown in FIG. 4. FIG. 4(a) shows experimentally measured resist lines400 having a more complicated shape, and with an estimated initialcontour 410 shown as a dotted white line. This initial contour 410 isshown more clearly in FIG. 4(b). FIG. 4(c) and (d) show the same stepsas FIG. 2(c) and (d) for this more complex contour 410. Despite thecontour 410 being arbitrary shaped, the image can be essentiallyunfolded (transformed) along this contour. In this unfolding, the localnormal to the contour is interpolated and sampled. At around the centerof FIG. 4(c), a varying SEM-signal 420 can clearly be observed. Thisvarying SEM-signal 420 corresponds to the tip of the resist line beingconsidered in FIG. 4(a), and is caused by the contour 410 not properlyfollowing the geometry at this tip. Averaging parallel to the wholecontour would, for this example, likely result in an incorrectreference-SEM signal at the tip of the resist line, and possibly wouldalso be incorrect for the whole resist line. However, it is desirable toaverage out some of the noise which is present. Therefore, a Gaussianblurring is applied to FIG. 4(c) (e.g., with a sigma of 5 nm) in thedirection parallel to the contour, to obtain the reference-SEM signal430 of FIG. 4(d). It can be observed that reference-SEM signal 430 hasan improved signal to noise ratio, while the tip region is still clearlydistinguishable. Again, no filtering is done in the perpendiculardirection. The columns of FIG. 4(d) are again assumed to be the localreference-SEM signals and are fitted to the identical columns of to FIG.4(c), allowing only a shift in height difference between the columns(i.e., a cross correlation between the columns of the two images), so asto redefine the contour. The obtained shifts of the column heightsrepresent the displacements and combined (optionally) with thresholdingof the edge position in (c), they provide the edge position shown as thenew contour line 440 (FIG. 4(e) and FIG. 4(f)) which better matches theactual contour of the feature 400.

The noise in the reference SEM-signal could be further reduced byfitting the signal with a spline function, such that the SEM signalwithout noise is preserved as much as possible. This can becomeparticulaly important when the method is performed iteratively, becausethe contours may begin also to align with the noise present in thereference SEM signal.

In summary, the proposed methods for detecting geometrical edgesdescribed herein takes a reference signal (e.g., reference edge orreference-SEM signal) from the actual image (e.g., the actual SEM image)on which an edge position is being detected, by unfolding an initialcontour. This is an improvement over methods such as described in U.S.Pat. No. 7,269,287 B2 which obtains reference-SEM signals from areference target, and only for examples of straight features andcylindrical symmetric features. In cases where LER is severe or wherethe initially guessed contour is inaccurate, this approach can be usediteratively, in the sense that the reference-SEM signal can beoptimized. Determining the local reference-SEM signals by means ofGaussian blurring parallel to the contour is robust against materialvariations and changing SEM-settings, especially when the blurringlength is taken to be equal or smaller than the beam width used in theSEM hardware. Also, the reference-SEM signal is obtained from an areaaround the initial contour, while in U.S. Pat. No. 7,269,287, theso-called white-band is used, which is not always well defined, or evenpresent. It is believed that this method can locate an edge on asub-pixel resolution with a higher accuracy and precision than possiblewith typically used thresholding methods, particularly when severe LERis present.

The proposed methods are highly flexible; while many CD-SEM analysistools can only be applied to a single use-case with well definedgeometry, these methods allow analysis of arbitrary complex shapedfeatures. This is particularly important for edge placement errormetrology.

The embodiments may further be described using the following clauses:

-   1. A method of determining an edge position relating to an edge of a    feature comprised within an image which comprises noise; said method    comprising:-   determining a reference signal from said image; and-   determining said edge position with respect to said reference    signal.-   2. A method according to clause 1, wherein the image has been    obtained using scanning electron microscopy metrology.-   3. A method according to clause 1 or 2, wherein said determining a    reference signal from said image comprises-   applying a 1-dimensional low-pass filter to said image in a    direction parallel to an initial contour, to-   obtain a filtered image comprising said reference signal.-   4. A method according to clause 3, comprising the step of estimating    the initial contour such that the initial contour comprises an    initial estimate of the edge being determined.-   5. A method according to clause 3 or 4, wherein said 1-dimensional    low-pass filter comprises a 1-dimensional Gaussian blur.-   6. A method according to clause 5, wherein a blurring length of the    Gaussian blur is equal or smaller than a beam width of a beam used    to obtain the image.-   7. A method according to any of clauses 3 to 6, wherein, prior to    application of the 1-dimensional low-pass filter, the method    comprises transforming at least a part of the image including said    edge, to obtain a transformed image in a transformed space    comprising a first dimension defined as parallel to the initial    contour and a second dimension defined as perpendicular to the    initial contour.-   8. A method according to clause 7, wherein only an area less than 10    nm either side of said initial contour is transformed to obtain said    transformed image.-   9. A method according to clause 7 or 8, comprising matching one of    said filtered image and said transformed image to the other of said    filtered image and said transformed image to determine a matched    contour, said matched contour comprising a matched estimate of said    edge position.-   10. A method according to clause 9, wherein said matching comprises    matching said filtered image to said transformed image on a    column-by-column basis.-   11. A method according to clause 10, wherein each column is defined    by the width of a pixel of said image.-   12. A method according to clause 10 or 11, wherein said matching    comprises a cross-correlation of the columns of the filtered image    and the corresponding columns of the transformed image.-   13. A method according to clause 12, wherein the cross-correlation    comprises only shifting the columns relative to each other along the    column direction to obtain the best match between the filtered image    and the transformed image.-   14. A method according to any of clauses 9 to 13, comprising an    additional thresholding step to the matched contour, based on a    threshold value defining the edge position, so as to obtain a    thresholded contour, said thresholded contour comprising a    thresholded estimate of said edge position.-   15. A method according to any of clauses 9 to 14, comprising    performing the method iteratively by performing at least one    additional iteration of said method, using the matched contour or    thresholded contour as the initial contour for each additional    iteration.-   16. A method according to any preceding clause, wherein said image    is obtained for measurement of a parameter relating to the feature    so as to monitor performance of a lithographic process for forming    said feature.-   17. A method according to clause 16, wherein said parameter    comprises one or more of: critical dimension, line edge roughness,    line width roughness, local critical dimension uniformity and edge    placement error.-   18. A method according to any preceding clause, comprising    performing a further noise reduction step on said reference signal    by fitting a spline function to the reference signal which maximizes    signal to noise.-   19. A computing apparatus comprising a processor, and being    configured to perform the method of any preceding clause.-   20. A scanning electron microscopy inspection apparatus being    operable to image one or more features on a substrate, and    comprising the computing apparatus of clause 19.-   21. A computer program comprising program instructions operable to    perform the method of any of clauses 1 to 18 when run on a suitable    apparatus.-   22. A non-transient computer program carrier comprising the computer    program of clause 21.

The terms “radiation” and “beam” used in relation to the lithographicapparatus encompass all types of electromagnetic radiation, includingultraviolet (UV) radiation (e.g., having a wavelength of or about 365,355, 248, 193, 157 or 126 nm) and extreme ultra-violet (EUV) radiation(e.g., having a wavelength in the range of 5-20 nm), as well as particlebeams, such as ion beams or electron beams.

The term “lens”, where the context allows, may refer to any one orcombination of various types of optical components, includingrefractive, reflective, magnetic, electromagnetic and electrostaticoptical components.

As used herein, unless specifically stated otherwise, the term “or”encompasses all possible combinations, except where infeasible. Forexample, if it is stated that a component may include A or B, then,unless specifically stated otherwise or infeasible, the component mayinclude A, or B, or A and B. As a second example, if it is stated that acomponent may include A, B, or C, then, unless specifically statedotherwise or infeasible, the component may include A, or B, or C, or Aand B, or A and C, or B and C, or A and B and C.

The foregoing description of the specific embodiments will so fullyreveal the general nature of the disclosed embodiments that others can,by applying knowledge within the skill of the art, readily modify oradapt for various applications such specific embodiments, without undueexperimentation, without departing from the general concept of thepresent disclosure. Therefore, such adaptations and modifications areintended to be within the meaning and range of equivalents of thedisclosed embodiments, based on the teaching and guidance presentedherein. It is to be understood that the phraseology or terminologyherein is for the purpose of description by example, and not oflimitation, such that the terminology or phraseology of the presentspecification is to be interpreted by the skilled artisan in light ofthe teachings and guidance.

The breadth and scope of the embodiments of the present disclosureshould not be limited by any of the above-described exemplaryembodiments but should be defined only in accordance with the followingclaims and their equivalents.

1. A method of determining an edge position relating to an edge of afeature comprised within an image that comprises noise, the methodcomprising: determining a reference signal from the image; anddetermining the edge position with respect to the reference signal. 2.The method of claim 1, wherein the image has been obtained usingscanning electron microscopy metrology.
 3. The method of claim 1,wherein determining the reference signal from the image comprisesapplying a 1-dimensional low-pass filter to the image in a directionparallel to an initial contour, to obtain a filtered image comprisingthe reference signal.
 4. The method of claim 3, further comprisingestimating the initial contour such that the initial contour comprisesan initial estimate of the edge being determined.
 5. The method of claim3, wherein the 1-dimensional low-pass filter comprises a 1-dimensionalGaussian blur.
 6. The method of claim 3, wherein, prior to applicationof the 1-dimensional low-pass filter, the method further comprisestransforming at least a part of the image including the edge, to obtaina transformed image in a transformed space comprising a first dimensiondefined as parallel to the initial contour and a second dimensiondefined as perpendicular to the initial contour.
 7. The method of claim6, further comprising matching one of the filtered image and thetransformed image to the other of the filtered image and the transformedimage to determine a matched contour, the matched contour comprising amatched estimate of the edge position.
 8. The method of claim 7, whereinmatching comprises matching the filtered image to the transformed imageon a column-by-column basis, and wherein each column is defined by thewidth of a pixel of the image.
 9. The method of claim 8, whereinmatching comprises a cross-correlation of the columns of the filteredimage and the corresponding columns of the transformed image.
 10. Themethod of claim 9, wherein the cross-correlation comprises only shiftingthe columns relative to each other along the column direction to obtainthe best match between the filtered image and the transformed image. 11.The method of claim 7, comprising performing the method iteratively byperforming at least one additional iteration of the method, using thematched contour or thresholded contour as the initial contour for eachadditional iteration.
 12. The method of claim 1, wherein the image isobtained for measurement of a parameter relating to the feature so as tomonitor performance of a lithographic process for forming the feature.13. The method of claim 12, wherein the parameter comprises at least oneof: critical dimension, line edge roughness, line width roughness, localcritical dimension uniformity, or edge placement error.
 14. A scanningelectron microscopy inspection apparatus being operable to image afeature on a substrate, the apparatus comprising: a memory storing a setof instructions; and one or more processors configured to execute theset of instructions to cause the apparatus to perform: determining areference signal from the image; and determining the edge position withrespect to the reference signal.
 15. The apparatus of claim 14, whereindetermining a reference signal from the image comprises the one or moreprocessors are configured to execute the set of instructions to causethe apparatus to further perform: applying a 1-dimensional low-passfilter to the image in a direction parallel to an initial contour, toobtain a filtered image comprising the reference signal.
 16. Theapparatus of claim 14, wherein the image is obtained for measurement ofa parameter relating to the feature so as to monitor performance of alithographic process for forming the feature.
 17. A non-transitorycomputer readable medium storing a set of instructions that areexecutable by one or more processors of an apparatus to cause theapparatus to perform a method for determining an edge position relatingto an edge of a feature comprised within an image that comprises noise,the method comprising: determining a reference signal from the image;and determining the edge position with respect to the reference signal.18. The non-transitory computer readable medium of claim 14, whereindetermining a reference signal from the image comprises applying a1-dimensional low-pass filter to the image in a direction parallel to aninitial contour, to obtain a filtered image comprising the referencesignal.
 19. The non-transitory computer readable medium of claim 14,wherein the image is obtained for measurement of a parameter relating tothe feature so as to monitor performance of a lithographic process forforming the feature.
 20. The non-transitory computer readable medium ofclaim 19, wherein the parameter comprises at least one of of: criticaldimension, line edge roughness, line width roughness, local criticaldimension uniformity, or edge placement error.